We investigate the influence of blurred ways on pattern recognition of a Barabasi-Albert scale-free Hopfield neural network （SFHN） with a small amount of errors. Pattern recognition is an important function of infor...We investigate the influence of blurred ways on pattern recognition of a Barabasi-Albert scale-free Hopfield neural network （SFHN） with a small amount of errors. Pattern recognition is an important function of information processing in brain. Due to heterogeneous degree of scale-free network, different blurred ways have different influences on pattern recognition with same errors. Simulation shows that among partial recognition, the larger loading ratio （the number of patterns to average degree P/ （k） ） is, the smaller the overlap of SFHN is. The influence of directed （large） way is largest and the directed （small） way is smallest while random way is intermediate between them. Under the ratio of the numbers of stored patterns to the size of the network PIN is less than O. 1 conditions, there are three families curves of the overlap corresponding to directed （small）, random and directed （large） blurred ways of patterns and these curves are not associated with the size of network and the number of patterns. This phenomenon only occurs in the SFHN. These conclusions are benefit for understanding the relation between neural network structure and brain function.展开更多
In imaging on moving target, it is easy to get space- variant blurred image. In order to recover the image and gain recognizable target, an approach to recover the space-variant blurred image is presented based on ima...In imaging on moving target, it is easy to get space- variant blurred image. In order to recover the image and gain recognizable target, an approach to recover the space-variant blurred image is presented based on image segmentation. Be- cause of motion blur＇s convolution process, the pixels of observed image＇s target and background will be displaced and piled up to produce two superposition regions. As a result, the neighbor- ing pixels in the superposition regions will have similar grey level change. According to the pixel＇s motion-blur character, the target＇s blurred edge of superposition region could be detected. Canny operator can be recurred to detect the target edge which parallels the motion blur direction. Then in the segmentation process, the whole target image which has the character of integral convolution between motion blur and real target image can be obtained. At last, the target image is restored by deconvolution algorithms with adding zeros. The restoration result indicates that the approach can effectively solve the kind of problem of space-variant motion blurred image restoration.展开更多
The 3D reconstruction using deep learning-based intelligent systems can provide great help for measuring an individual’s height and shape quickly and accurately through 2D motion-blurred images.Generally,during the a...The 3D reconstruction using deep learning-based intelligent systems can provide great help for measuring an individual’s height and shape quickly and accurately through 2D motion-blurred images.Generally,during the acquisition of images in real-time,motion blur,caused by camera shaking or human motion,appears.Deep learning-based intelligent control applied in vision can help us solve the problem.To this end,we propose a 3D reconstruction method for motion-blurred images using deep learning.First,we develop a BF-WGAN algorithm that combines the bilateral filtering(BF)denoising theory with a Wasserstein generative adversarial network(WGAN)to remove motion blur.The bilateral filter denoising algorithm is used to remove the noise and to retain the details of the blurred image.Then,the blurred image and the corresponding sharp image are input into the WGAN.This algorithm distinguishes the motion-blurred image from the corresponding sharp image according to the WGAN loss and perceptual loss functions.Next,we use the deblurred images generated by the BFWGAN algorithm for 3D reconstruction.We propose a threshold optimization random sample consensus(TO-RANSAC)algorithm that can remove the wrong relationship between two views in the 3D reconstructed model relatively accurately.Compared with the traditional RANSAC algorithm,the TO-RANSAC algorithm can adjust the threshold adaptively,which improves the accuracy of the 3D reconstruction results.The experimental results show that our BF-WGAN algorithm has a better deblurring effect and higher efficiency than do other representative algorithms.In addition,the TO-RANSAC algorithm yields a calculation accuracy considerably higher than that of the traditional RANSAC algorithm.展开更多
A novel single-channel blind separation algorithm for permuted motion blurred images is proposed by using blind restoration in this paper. Both the motion direction and the length of the point spread function （PSF） ...A novel single-channel blind separation algorithm for permuted motion blurred images is proposed by using blind restoration in this paper. Both the motion direction and the length of the point spread function （PSF） are estimated by Radon transformation and extrema a detection. Using the estimated blur parameters, the permuted image is restored by performing the L-R blind restoration method. The permutation mixing matrices can be accurately estimated by classifying the ringing effect in the restored image, thereby the source images can be separated. Simulation results show a better separation efficiency for the permuted motion blurred image with various permutation operations. The proposed algorithm indicates a better performance on the robustness against Gaussian noise and lossy JPEG compression.展开更多
In this paper image with horizontal motion blur, vertical motion blur and angled motion blur are considered. We construct several difference schemes to the highly nonlinear term △↓.（△↓u/√｜△↓｜^2＋β） of the ...In this paper image with horizontal motion blur, vertical motion blur and angled motion blur are considered. We construct several difference schemes to the highly nonlinear term △↓.（△↓u/√｜△↓｜^2＋β） of the total variation-based image motion deblurring problem. The large nonlinear system is linearized by fixed point iteration method. An algebraic multigrid method with Krylov subspace acceleration is used to solve the corresponding linear equations as in [7]. The algorithms can restore the image very well. We give some numerical experiments to demonstrate that our difference schemes are efficient and robust.展开更多
A novel motion-blur-based method for measuring the angular amplitude of a high-frequency rotational vibration is schemed. The proposed approach combines the active vision concept and the mechanism of motion-from-blur,...A novel motion-blur-based method for measuring the angular amplitude of a high-frequency rotational vibration is schemed. The proposed approach combines the active vision concept and the mechanism of motion-from-blur, generates motion blur on the image plane actively by extending exposure time, and utilizes the motion blur information in polar images to estimate the angular amplitude of a high-frequency rotational vibration. This method obtains the analytical results of the angular vibration amplitude from the geometric moments of a motion blurred polar image and an unblurred image for reference. Experimental results are provided to validate the presented scheme.展开更多
As for machine vision-based intelligent system in the application of discriminating and sorting the sex of silkworm pupae,the tail gonad was the unique physiological feature.However,motion blur,resulting from the live...As for machine vision-based intelligent system in the application of discriminating and sorting the sex of silkworm pupae,the tail gonad was the unique physiological feature.However,motion blur,resulting from the live silkworm pupa’s writhing motion at the moment of capturing image,could lose textures and structures(such as edge and tail gonad etc.)dramatically,which casted great challenges for sex identification.To increase the image quality and relieve the difficulty of discrimination caused by motion blur,an effective approach that including three stages was proposed in this work.In the image prediction stage,first sharp edges were acquired by using filtering techniques.Then the initial blur kernel was computed with Gaussian prior.The coarse version latent image was deconvoluted in the Fourier domain.In the kernel refinement stage,the Radon transform was applied to estimate the accurate kernel.In the final restoration step,a TV-L1 deconvolution model was carried out to obtain a better result.The experimental results showed that benefiting from the prediction step and kernel refinement step,the kernel was more accurate and the recovered image contained much more textures.It revealed that the proposed method was useful in removing the motion blur.Furthermore,the method could also be applied to other fields.展开更多
Motion blur due to camera shake during exposure is one of the most common reasons of image degradation, which usually reduces the quality of photographs seriously. Based on the statistical properties of the natural im...Motion blur due to camera shake during exposure is one of the most common reasons of image degradation, which usually reduces the quality of photographs seriously. Based on the statistical properties of the natural image＇s gradient and the blur kernel, a blind deconvolution algorithm is proposed to restore the motion-blurred image caused by camera shake, adopting the variational Bayesian estimation theory. In addition, the ring effect is one problem that is not avoided in the process of image deconvolution, and usually makes the visual effect of the restored image badly. So a dering method is put forward based on the sub-region detection and fuzzy filter. Tested on the real blurred photographs, the experimental results show that the proposed algorithm of blind image deconvolution can remove the camera-shake motion blur from the degraded image effectively, and can eliminate the ring effect better, while preserve the edges and details of the image well.展开更多
The rotary motion deblurring is an inevitable procedure when the imaging seeker is mounted in the rotating missiles.Traditional rotary motion deblurring methods suffer from ringing artifacts and noise,especially for l...The rotary motion deblurring is an inevitable procedure when the imaging seeker is mounted in the rotating missiles.Traditional rotary motion deblurring methods suffer from ringing artifacts and noise,especially for large blur extents.To solve the above problems,we propose a progressive rotary motion deblurring framework consisting of a coarse deblurring stage and a refinement stage.In the first stage,we design an adaptive blur extents factor(BE factor)to balance noise suppression and details reconstruction.And a novel deconvolution model is proposed based on BE factor.In the second stage,a triplescale deformable module CNN(TDM-CNN)is designed to reduce the ringing artifacts,which can exploit the 2D information of an image and adaptively adjust spatial sampling locations.To establish a standard evaluation benchmark,a real-world rotary motion blur dataset is proposed and released,which includes rotary blurred images and corresponding ground truth images with different blur angles.Experimental results demonstrate that the proposed method outperforms the state-of-the-art models on synthetic and real-world rotary motion blur datasets.The code and dataset are available at https://github.com/JinhuiQin/RotaryDeblurring.展开更多
Multiplex environmental factors are generally expected to have significant effects on genetic diversity of plant populations.In this study,randomly amplified polymorphic DNA（RAPD） technique was used to reveal the ge...Multiplex environmental factors are generally expected to have significant effects on genetic diversity of plant populations.In this study,randomly amplified polymorphic DNA（RAPD） technique was used to reveal the genetic diversity in the same species of four populations collected from Niupidujuan（Rhododendron chrysanthum） at different altitudes,an endangered species,endemic to Northeast China.Initially,twenty informative and reproducible primers were chosen for final RAPD analysis.A total of 152 clear bands were obtained,including 143 polymorphic ones.With the help of POPGENE software,the poly rate was calculated to be 94.07% and the evenness of amplified bands for every primer was 6.8.Additionally,the mean observed number of alleles was 1.7265 with an effective number of 1.3608.An examination of the gene indicated a diversity of 0.2162 with an information diversity index of 0.3313.For these data,the clustering blurred analysis was performed with the aid of NTSYS-pc software to define the Nei＇s gene diversity and the Shannon information diversity index of the four plant populations.The relationships between the genetic diversity indexes on the one hand and the geographic and climatic factors on the other hand were estimated by the Pearson correlation with SPSS 11.0 software.The results of the correlation analysis show that there were significant（P〈0.05） or highly significant（P〈0.01） correlations between each of the genetic diversity indexes and the different temperature which were mainly caused by the altitude different populations located.These data highlight the importance of native populations in shaping the spatial genetic structure in Niupidujuan.展开更多
BACKGROUND Globally,although the jellyfish population has increased in recent years,ocular jellyfish stings remain an uncommon ophthalmic emergency,and have been rarely reported.According to a few previous reports,ocu...BACKGROUND Globally,although the jellyfish population has increased in recent years,ocular jellyfish stings remain an uncommon ophthalmic emergency,and have been rarely reported.According to a few previous reports,ocular jellyfish stings may cause anterior segment disorders,and most of these injuries were self-limited and spontaneously resolved within 24 to 48 h.CASE SUMMARY A brother and sister both presented with severe fundus complications several years after ocular jellyfish stings and both had prolonged blurred vision.To our knowledge,such fundus lesions induced by jellyfish stings have not been reported previously.CONCLUSION The fundus status of patients following ocular jellyfish stings should be carefully monitored in cases of irreversible ocular damage.展开更多
This paper introduces a new effective method to restore the uniform linear motion blurred im-age. The effect of the out-of-frame pixels on the blurring process and the estimate of these pixelsare analysed. The restora...This paper introduces a new effective method to restore the uniform linear motion blurred im-age. The effect of the out-of-frame pixels on the blurring process and the estimate of these pixelsare analysed. The restoration qualities of different deblurring methods are compared. Finally, theauthors come to a conclusion that it is impossible to determine the length of blurring movement infrequency domain.展开更多
A simulation method is proposed to predict the motion artifacts of plasma display panels （PDPs）. The method simulates the behavior of the human vision system when perceiving moving objects. The simulation is based o...A simulation method is proposed to predict the motion artifacts of plasma display panels （PDPs）. The method simulates the behavior of the human vision system when perceiving moving objects. The simulation is based on the measured temporal light properties of the display for each gray level and each phosphor. Both the effect of subfield arrangement and phosphor decay are involved. A novel algorithm is proposed to improve the calculation speed. The simulation model manages to predict the appearance of the motion image perceived by a human with a still image. The results are validated by a set of perceptual evaluation experiments. This rapid and accurate prediction of motion artifacts enables objective characterization of the PDP performance in this aspect.展开更多
BACKGROUND Acquired prosopagnosia is a rare condition characterized by the loss of familiarity with previously known faces and the inability to recognize new ones.It usually occurs after the onset of brain lesions suc...BACKGROUND Acquired prosopagnosia is a rare condition characterized by the loss of familiarity with previously known faces and the inability to recognize new ones.It usually occurs after the onset of brain lesions such as in a stroke.The initial identification of prosopagnosia generally relies on a patient’s self-report,which can be challenging if it lacks an associated chief complaint.There were few cases of prosopagnosia presenting purely as eye symptoms in the previous literature confirmed by functional magnetic resonance imaging(MRI).CASE SUMMARY We present a case of delayed diagnosis of prosopagnosia after a right hemisphere stroke in an elderly man whose chief complaint was persistent and progressive"blurred vision"without facial recognition impairment.Ophthalmic tests revealed a homonymous left upper quadrantanopia,with normal visual acuity.He was found by accident to barely recognize familiar faces.The patient showed severe deficit in face recognition and perception tests,and mild memory loss in neuropsychological assessments.Further functional MRI revealed the visual recognition deficits were face-specific.After behavioral intervention,the patient started to rely on other cues to compensate for poor facial recognition.His prosopagnosia showed no obvious improvement eight months after the stroke,which had negative impact on his social network.CONCLUSION Our case demonstrates that the presentation of prosopagnosia can be atypical,and visual difficulties might be a clinical manifestation solely of prosopagnosia,which emphasizes the importance of routinely considering face recognition impairment among elderly patients with brain lesions.展开更多
Blur is produced in a digital image due to low passfiltering,moving objects or defocus of the camera lens during capture.Image viewers are annoyed by blur artefact and the image's perceived quality suffers as a re...Blur is produced in a digital image due to low passfiltering,moving objects or defocus of the camera lens during capture.Image viewers are annoyed by blur artefact and the image's perceived quality suffers as a result.The high-quality input is relevant to communication service providers and imaging product makers because it may help them improve their processes.Human-based blur assessment is time-consuming,expensive and must adhere to subjective evaluation standards.This paper presents a revolutionary no-reference blur assessment algorithm based on reblurring blurred images using a special mask developed with a Markov basis and Laplacefilter.Thefinal blur score of blurred images has been calculated from the local variation in horizontal and vertical pixel intensity of blurred and re-blurred images.The objective scores are generated by applying proposed algorithm on the two image databases i.e.,Laboratory for image and video engineering(LIVE)database and Tampere image database(TID 2013).Finally,on the basis of objective and subjective scores performance analysis is done in terms of Pearson linear correlation coefficient(PLCC),Spearman rank-order correlation coefficient(SROCC),Mean absolute error(MAE),Root mean square error(RMSE)and Outliers ratio(OR).The existing no-reference blur assessment algorithms have been used various methods for the evaluation of blur from no-reference image such as Just noticeable blur(JNB),Cumulative Probability Distribution of Blur Detection(CPBD)and Edge Model based Blur Metric(EMBM).The results illustrate that the proposed method was successful in predicting high blur scores with high accuracy as compared to existing no-reference blur assessment algorithms such as JNB,CPBD and EMBM algorithms.展开更多
基金Supported by "Qing Lan" Talent Engineering Funds by Lanzhou Jiaotong University under Grant No. QL-08-18A
文摘We investigate the influence of blurred ways on pattern recognition of a Barabasi-Albert scale-free Hopfield neural network （SFHN） with a small amount of errors. Pattern recognition is an important function of information processing in brain. Due to heterogeneous degree of scale-free network, different blurred ways have different influences on pattern recognition with same errors. Simulation shows that among partial recognition, the larger loading ratio （the number of patterns to average degree P/ （k） ） is, the smaller the overlap of SFHN is. The influence of directed （large） way is largest and the directed （small） way is smallest while random way is intermediate between them. Under the ratio of the numbers of stored patterns to the size of the network PIN is less than O. 1 conditions, there are three families curves of the overlap corresponding to directed （small）, random and directed （large） blurred ways of patterns and these curves are not associated with the size of network and the number of patterns. This phenomenon only occurs in the SFHN. These conclusions are benefit for understanding the relation between neural network structure and brain function.
文摘In imaging on moving target, it is easy to get space- variant blurred image. In order to recover the image and gain recognizable target, an approach to recover the space-variant blurred image is presented based on image segmentation. Be- cause of motion blur＇s convolution process, the pixels of observed image＇s target and background will be displaced and piled up to produce two superposition regions. As a result, the neighbor- ing pixels in the superposition regions will have similar grey level change. According to the pixel＇s motion-blur character, the target＇s blurred edge of superposition region could be detected. Canny operator can be recurred to detect the target edge which parallels the motion blur direction. Then in the segmentation process, the whole target image which has the character of integral convolution between motion blur and real target image can be obtained. At last, the target image is restored by deconvolution algorithms with adding zeros. The restoration result indicates that the approach can effectively solve the kind of problem of space-variant motion blurred image restoration.
基金the National Natural Science Foundation of China under Grant 61902311in part by the Japan Society for the Promotion of Science(JSPS)Grants-in-Aid for Scientific Research(KAKENHI)under Grant JP18K18044.
文摘The 3D reconstruction using deep learning-based intelligent systems can provide great help for measuring an individual’s height and shape quickly and accurately through 2D motion-blurred images.Generally,during the acquisition of images in real-time,motion blur,caused by camera shaking or human motion,appears.Deep learning-based intelligent control applied in vision can help us solve the problem.To this end,we propose a 3D reconstruction method for motion-blurred images using deep learning.First,we develop a BF-WGAN algorithm that combines the bilateral filtering(BF)denoising theory with a Wasserstein generative adversarial network(WGAN)to remove motion blur.The bilateral filter denoising algorithm is used to remove the noise and to retain the details of the blurred image.Then,the blurred image and the corresponding sharp image are input into the WGAN.This algorithm distinguishes the motion-blurred image from the corresponding sharp image according to the WGAN loss and perceptual loss functions.Next,we use the deblurred images generated by the BFWGAN algorithm for 3D reconstruction.We propose a threshold optimization random sample consensus(TO-RANSAC)algorithm that can remove the wrong relationship between two views in the 3D reconstructed model relatively accurately.Compared with the traditional RANSAC algorithm,the TO-RANSAC algorithm can adjust the threshold adaptively,which improves the accuracy of the 3D reconstruction results.The experimental results show that our BF-WGAN algorithm has a better deblurring effect and higher efficiency than do other representative algorithms.In addition,the TO-RANSAC algorithm yields a calculation accuracy considerably higher than that of the traditional RANSAC algorithm.
基金Project supported by the National Natural Science Foundation of China (Grant No.60872114)the Shanghai Leading Academic Discipline Project (Grant No.S30108)the Graduate Student Innovation Foundation of Shanghai University (Grant No.SHUCX101086)
文摘A novel single-channel blind separation algorithm for permuted motion blurred images is proposed by using blind restoration in this paper. Both the motion direction and the length of the point spread function （PSF） are estimated by Radon transformation and extrema a detection. Using the estimated blur parameters, the permuted image is restored by performing the L-R blind restoration method. The permutation mixing matrices can be accurately estimated by classifying the ringing effect in the restored image, thereby the source images can be separated. Simulation results show a better separation efficiency for the permuted motion blurred image with various permutation operations. The proposed algorithm indicates a better performance on the robustness against Gaussian noise and lossy JPEG compression.
文摘In this paper image with horizontal motion blur, vertical motion blur and angled motion blur are considered. We construct several difference schemes to the highly nonlinear term △↓.（△↓u/√｜△↓｜^2＋β） of the total variation-based image motion deblurring problem. The large nonlinear system is linearized by fixed point iteration method. An algebraic multigrid method with Krylov subspace acceleration is used to solve the corresponding linear equations as in [7]. The algorithms can restore the image very well. We give some numerical experiments to demonstrate that our difference schemes are efficient and robust.
基金This project is supported by National Natural Science Foundation of China (No. 50375099, No. 50390064)
文摘A novel motion-blur-based method for measuring the angular amplitude of a high-frequency rotational vibration is schemed. The proposed approach combines the active vision concept and the mechanism of motion-from-blur, generates motion blur on the image plane actively by extending exposure time, and utilizes the motion blur information in polar images to estimate the angular amplitude of a high-frequency rotational vibration. This method obtains the analytical results of the angular vibration amplitude from the geometric moments of a motion blurred polar image and an unblurred image for reference. Experimental results are provided to validate the presented scheme.
基金The research was financially supported by Chongqing Science and Technology Commission Projects under Grant No.cstc2013yykfA80015 and Grant No.cstc2017shms-xdny80080Fundamental Research Funds for the Central Universities under Grant No.XDJK2016A007,XDJK2018D011Doctoral Scientific Research Foundation of Southwest University Project Grant No.SWU114109.
文摘As for machine vision-based intelligent system in the application of discriminating and sorting the sex of silkworm pupae,the tail gonad was the unique physiological feature.However,motion blur,resulting from the live silkworm pupa’s writhing motion at the moment of capturing image,could lose textures and structures(such as edge and tail gonad etc.)dramatically,which casted great challenges for sex identification.To increase the image quality and relieve the difficulty of discrimination caused by motion blur,an effective approach that including three stages was proposed in this work.In the image prediction stage,first sharp edges were acquired by using filtering techniques.Then the initial blur kernel was computed with Gaussian prior.The coarse version latent image was deconvoluted in the Fourier domain.In the kernel refinement stage,the Radon transform was applied to estimate the accurate kernel.In the final restoration step,a TV-L1 deconvolution model was carried out to obtain a better result.The experimental results showed that benefiting from the prediction step and kernel refinement step,the kernel was more accurate and the recovered image contained much more textures.It revealed that the proposed method was useful in removing the motion blur.Furthermore,the method could also be applied to other fields.
文摘Motion blur due to camera shake during exposure is one of the most common reasons of image degradation, which usually reduces the quality of photographs seriously. Based on the statistical properties of the natural image＇s gradient and the blur kernel, a blind deconvolution algorithm is proposed to restore the motion-blurred image caused by camera shake, adopting the variational Bayesian estimation theory. In addition, the ring effect is one problem that is not avoided in the process of image deconvolution, and usually makes the visual effect of the restored image badly. So a dering method is put forward based on the sub-region detection and fuzzy filter. Tested on the real blurred photographs, the experimental results show that the proposed algorithm of blind image deconvolution can remove the camera-shake motion blur from the degraded image effectively, and can eliminate the ring effect better, while preserve the edges and details of the image well.
基金the National Natural Science Foundation of China under Grant 62075169,Grant 62003247,and Grant 62061160370the Hubei Province Key Research and Development Program under Grant 2021BBA235the Zhuhai Basic and Applied Basic Research Foundation under Grant ZH22017003200010PWC.
文摘The rotary motion deblurring is an inevitable procedure when the imaging seeker is mounted in the rotating missiles.Traditional rotary motion deblurring methods suffer from ringing artifacts and noise,especially for large blur extents.To solve the above problems,we propose a progressive rotary motion deblurring framework consisting of a coarse deblurring stage and a refinement stage.In the first stage,we design an adaptive blur extents factor(BE factor)to balance noise suppression and details reconstruction.And a novel deconvolution model is proposed based on BE factor.In the second stage,a triplescale deformable module CNN(TDM-CNN)is designed to reduce the ringing artifacts,which can exploit the 2D information of an image and adaptively adjust spatial sampling locations.To establish a standard evaluation benchmark,a real-world rotary motion blur dataset is proposed and released,which includes rotary blurred images and corresponding ground truth images with different blur angles.Experimental results demonstrate that the proposed method outperforms the state-of-the-art models on synthetic and real-world rotary motion blur datasets.The code and dataset are available at https://github.com/JinhuiQin/RotaryDeblurring.
基金Supported by the Project of Development and Reform Commission of Jilin Province,China
文摘Multiplex environmental factors are generally expected to have significant effects on genetic diversity of plant populations.In this study,randomly amplified polymorphic DNA（RAPD） technique was used to reveal the genetic diversity in the same species of four populations collected from Niupidujuan（Rhododendron chrysanthum） at different altitudes,an endangered species,endemic to Northeast China.Initially,twenty informative and reproducible primers were chosen for final RAPD analysis.A total of 152 clear bands were obtained,including 143 polymorphic ones.With the help of POPGENE software,the poly rate was calculated to be 94.07% and the evenness of amplified bands for every primer was 6.8.Additionally,the mean observed number of alleles was 1.7265 with an effective number of 1.3608.An examination of the gene indicated a diversity of 0.2162 with an information diversity index of 0.3313.For these data,the clustering blurred analysis was performed with the aid of NTSYS-pc software to define the Nei＇s gene diversity and the Shannon information diversity index of the four plant populations.The relationships between the genetic diversity indexes on the one hand and the geographic and climatic factors on the other hand were estimated by the Pearson correlation with SPSS 11.0 software.The results of the correlation analysis show that there were significant（P〈0.05） or highly significant（P〈0.01） correlations between each of the genetic diversity indexes and the different temperature which were mainly caused by the altitude different populations located.These data highlight the importance of native populations in shaping the spatial genetic structure in Niupidujuan.
文摘BACKGROUND Globally,although the jellyfish population has increased in recent years,ocular jellyfish stings remain an uncommon ophthalmic emergency,and have been rarely reported.According to a few previous reports,ocular jellyfish stings may cause anterior segment disorders,and most of these injuries were self-limited and spontaneously resolved within 24 to 48 h.CASE SUMMARY A brother and sister both presented with severe fundus complications several years after ocular jellyfish stings and both had prolonged blurred vision.To our knowledge,such fundus lesions induced by jellyfish stings have not been reported previously.CONCLUSION The fundus status of patients following ocular jellyfish stings should be carefully monitored in cases of irreversible ocular damage.
文摘This paper introduces a new effective method to restore the uniform linear motion blurred im-age. The effect of the out-of-frame pixels on the blurring process and the estimate of these pixelsare analysed. The restoration qualities of different deblurring methods are compared. Finally, theauthors come to a conclusion that it is impossible to determine the length of blurring movement infrequency domain.
文摘A simulation method is proposed to predict the motion artifacts of plasma display panels （PDPs）. The method simulates the behavior of the human vision system when perceiving moving objects. The simulation is based on the measured temporal light properties of the display for each gray level and each phosphor. Both the effect of subfield arrangement and phosphor decay are involved. A novel algorithm is proposed to improve the calculation speed. The simulation model manages to predict the appearance of the motion image perceived by a human with a still image. The results are validated by a set of perceptual evaluation experiments. This rapid and accurate prediction of motion artifacts enables objective characterization of the PDP performance in this aspect.
基金Supported by Fujian Science and Technology Innovation Joint Major Project,No.2019Y9027Fujian Major Projects on Science and Technology for Social Development,No.2016YZ0001.
文摘BACKGROUND Acquired prosopagnosia is a rare condition characterized by the loss of familiarity with previously known faces and the inability to recognize new ones.It usually occurs after the onset of brain lesions such as in a stroke.The initial identification of prosopagnosia generally relies on a patient’s self-report,which can be challenging if it lacks an associated chief complaint.There were few cases of prosopagnosia presenting purely as eye symptoms in the previous literature confirmed by functional magnetic resonance imaging(MRI).CASE SUMMARY We present a case of delayed diagnosis of prosopagnosia after a right hemisphere stroke in an elderly man whose chief complaint was persistent and progressive"blurred vision"without facial recognition impairment.Ophthalmic tests revealed a homonymous left upper quadrantanopia,with normal visual acuity.He was found by accident to barely recognize familiar faces.The patient showed severe deficit in face recognition and perception tests,and mild memory loss in neuropsychological assessments.Further functional MRI revealed the visual recognition deficits were face-specific.After behavioral intervention,the patient started to rely on other cues to compensate for poor facial recognition.His prosopagnosia showed no obvious improvement eight months after the stroke,which had negative impact on his social network.CONCLUSION Our case demonstrates that the presentation of prosopagnosia can be atypical,and visual difficulties might be a clinical manifestation solely of prosopagnosia,which emphasizes the importance of routinely considering face recognition impairment among elderly patients with brain lesions.
文摘Blur is produced in a digital image due to low passfiltering,moving objects or defocus of the camera lens during capture.Image viewers are annoyed by blur artefact and the image's perceived quality suffers as a result.The high-quality input is relevant to communication service providers and imaging product makers because it may help them improve their processes.Human-based blur assessment is time-consuming,expensive and must adhere to subjective evaluation standards.This paper presents a revolutionary no-reference blur assessment algorithm based on reblurring blurred images using a special mask developed with a Markov basis and Laplacefilter.Thefinal blur score of blurred images has been calculated from the local variation in horizontal and vertical pixel intensity of blurred and re-blurred images.The objective scores are generated by applying proposed algorithm on the two image databases i.e.,Laboratory for image and video engineering(LIVE)database and Tampere image database(TID 2013).Finally,on the basis of objective and subjective scores performance analysis is done in terms of Pearson linear correlation coefficient(PLCC),Spearman rank-order correlation coefficient(SROCC),Mean absolute error(MAE),Root mean square error(RMSE)and Outliers ratio(OR).The existing no-reference blur assessment algorithms have been used various methods for the evaluation of blur from no-reference image such as Just noticeable blur(JNB),Cumulative Probability Distribution of Blur Detection(CPBD)and Edge Model based Blur Metric(EMBM).The results illustrate that the proposed method was successful in predicting high blur scores with high accuracy as compared to existing no-reference blur assessment algorithms such as JNB,CPBD and EMBM algorithms.
